Limit theory for an explosive autoregressive process
Large sample properties are studied for a first-order autoregression (AR(1)) with a root greater than unity. It is shown that, contrary to the AR coefficient, the least-squares (LS) estimator of the intercept and its t-statistic are asymptotically normal without requiring the Gaussian error distribu...
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sg-smu-ink.soe_research-26182020-04-01T08:54:18Z Limit theory for an explosive autoregressive process WANG, Xiaohu YU, Jun Large sample properties are studied for a first-order autoregression (AR(1)) with a root greater than unity. It is shown that, contrary to the AR coefficient, the least-squares (LS) estimator of the intercept and its t-statistic are asymptotically normal without requiring the Gaussian error distribution, and hence an invariance principle applies. The coefficient based test and the t test have better power for testing the hypothesis of zero intercept in the explosive process than in the stationary process. 2015-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1619 info:doi/10.1016/j.econlet.2014.12.004 https://ink.library.smu.edu.sg/context/soe_research/article/2618/viewcontent/Yu_EL_2015.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Explosive model Intercept Invariance principle Bubbles Econometrics Economics |
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Explosive model Intercept Invariance principle Bubbles Econometrics Economics WANG, Xiaohu YU, Jun Limit theory for an explosive autoregressive process |
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Large sample properties are studied for a first-order autoregression (AR(1)) with a root greater than unity. It is shown that, contrary to the AR coefficient, the least-squares (LS) estimator of the intercept and its t-statistic are asymptotically normal without requiring the Gaussian error distribution, and hence an invariance principle applies. The coefficient based test and the t test have better power for testing the hypothesis of zero intercept in the explosive process than in the stationary process. |
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WANG, Xiaohu YU, Jun |
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WANG, Xiaohu YU, Jun |
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WANG, Xiaohu |
title |
Limit theory for an explosive autoregressive process |
title_short |
Limit theory for an explosive autoregressive process |
title_full |
Limit theory for an explosive autoregressive process |
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Limit theory for an explosive autoregressive process |
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Limit theory for an explosive autoregressive process |
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limit theory for an explosive autoregressive process |
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Institutional Knowledge at Singapore Management University |
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2015 |
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https://ink.library.smu.edu.sg/soe_research/1619 https://ink.library.smu.edu.sg/context/soe_research/article/2618/viewcontent/Yu_EL_2015.pdf |
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